A LRAAM-based Partial Order Function for Ontology Matching in the Context of Service Discovery

Hendrik Ludolph, Peter Kropf, Gilbert Babin

Abstract

The demand for Software as a Service is heavily increasing in the era of Cloud. With this demand comes a proliferation of third-party service offerings to fulfill it. It thus becomes crucial for organizations to find and select the right services to be integrated into their existing tool landscapes. Ideally, this is done automatically and continuously. The objective is to always provide the best possible support to changing business needs. In this paper, we explore an artificial neural network implementation, an LRAAM, as the specific oracle to control the selection process. We implemented a proof of concept and conducted experiments to explore the validity of the approach. We show that our implementation of the LRAAM performs correctly under specific parameters. We also identify limitations in using LRAAM in this context.

References

  1. Al-Said, G. and Abdallah, M. (2009). An arabic textto-speech system based on artificial neural networks. Journal of Computer Science, 5(3):207-213.
  2. Antoniou, G. and van Harmelen, F. (2008). A Semantic Web Primer. The MIT Press, Cambridge Massachusetts, 2 edition.
  3. Antoniou, G. and van Harmelen, F. (2009). Ontology web language: Owl. In Staab, S. and Studer, R., editors, Handbook on Ontologies, pages 91-110. Springer.
  4. Atencia, M., Euzenat, J., Pirrò, G., and Rousset, M.-C. (2011). Alignment-based trust for resource finding in semantic p2p networks. In The Semantic Web-ISWC 2011, pages 51-66. Springer.
  5. Blank, D., Meeden, L. A., and Marshall, J. B. (1992). Exploring the symbolic/subsymbolic continuum: A case study of RAAM. In The Symbolic and Connectionist Paradigms: Closing the Gap, pages 113-148. Erlbaum.
  6. Born, M., Drumm, C., Markovic, I., and Weber, I. (2007). SUPER - raising business process management back to the business level. ERCIM News, 2007(70).
  7. Bughin, J. and Chui, M. (2010). The rise of the networked enterprise: Web 2.0 finds its payday. McKinsey quarterly, 4:3-8.
  8. Chan, S. W. K. (2003). Dynamic context generation for natural language understanding: A multifaceted knowledge approach. IEEE Transactions on systems, man, and Cybernetics - Part A: Systems and Humans, 33(1):23-41.
  9. Cisco (2014). Cisco global cloud index: Forecast and methodology: 2013 - 2018. White paper, Cisco Systems Inc.
  10. de Gerlachey, M., Sperdutiz, A., and Staritaz, A. (1994). Using labeling raam to encode medical conceptual graphs. NNESMED'94 proceedings.
  11. Diallo, G. (2014). An effective method of large scale ontology matching. Journal of Biomedical Semantics, 5:44.
  12. Eder, J. and Wiggisser, K. (2007). Detecting changes in ontologies via DAG comparison. In Lecture Notes in Computer Science 4495, pages 21-35.
  13. Ellingsen, B. K. (1997). Distributed representations of object-oriented specifications for analogical mapping. Technical report, Citeseer.
  14. Erl, T. (2004). Service-oriented architecture: a field guide to integrating XML and web services. Prentice Hall PTR.
  15. Erl, T., Chelliah, P., Gee, C., Kress, J., Maier, B., Normann, H., Shuster, L., Trops, B., Utschig, C., Wik, P., and Winterberg, T. (2014). Next Generation SOA: A Concise Introduction to Service Technology & ServiceOrientation. The Prentice Hall Service Technology Series from Thomas Erl. Pearson Education.
  16. Euzenat, J. and Shvaiko, P. (2007). Ontology Matching. Springer.
  17. Euzenat, J. and Shvaiko, P. (2013). Ontology Matching. Springer, 2 edition.
  18. Fensel, D. and Bussler, C. (2002). The web service modeling framework wsmf. Electronic Commerce Research and Applications, 1(2):113-137.
  19. Fensel, D., Facca, F. M., Simperl, E., and Toma, I. (2011). Semantic web services. Springer Science & Business Media.
  20. Frank, R. and Cartwright, E. (2013). Microeconomics and Behaviour. McGraw Hill.
  21. Hinton, G., McClelland, J., and Rumelhart, D. (1986). Distributed representations, volume 1, pages 77-109. MIT Press.
  22. Hoang, H. H., Jung, J. J., and Tran, C. P. (2014). Ontologybased approaches for cross-enterprise collaboration: A literature review on semantic business process management. Enterprise Information Systems, 8(6):648- 664.
  23. Hoang, H. H. and Le, M. T. (2009). Bizkb: A conceptual framework for dynamic cross-enterprise collaboration. In Nguyen, N. T., Kowalczyk, R., and Chen, S.-M., editors, ICCCI, volume 5796 of Lecture Notes in Computer Science, pages 401-412. Springer.
  24. Hussain, M. A. and Mastan, M. (2014). A study on semantic web services and its significant trends. IJCER, 3(5):234-237.
  25. Izza, S. (2009). Integration of industrial information systems: from syntactic to semantic integration approaches. Enterprise Information Systems, 3(1):1-57.
  26. Kale, V. (2014). Guide to Cloud Computing for Business and Technology Managers: From Distributed Computing to Cloudware Applications. Taylor & Francis.
  27. Kotis, K., Vouros, G., and Stergiou, K. (2006). Towards automatic merging of domain ontologies: The hconemerge approach. Journal of Web Semantics (JWS), 4:60-79.
  28. LeCun, Y., Bengio, Y., and Hinton, G. (2015). Deep learning. Nature, 521(7553):436-444.
  29. Lehaney, B., Lovett, P., and Shah, M. (2011). Business information systems and technology: a primer. Routledge.
  30. Li, W., Raskin, R., and Goodchild, M. F. (2012). Semantic similarity measurement based on knowledge mining: An artificial neural net approach. International Journal of Geographical Information Science, 26(8):1415-1435.
  31. Ludolph, H., Kropf, P., and Babin, G. (2011). SoftwIre integration - an onto-neural perspective. In Babin, G., Stanoevska-Slabeva, K., and Kropf, P., editors, ETechnologies: Transformation in a Connected World - 5th International Conference (MCETECH 2011). Les Diablerets, Switzerland, January 23-26, 2011, Revised Selected Papers, number 78 in Lecture Notes in Business Information Processing, pages 116-130. Springer.
  32. Otero-Cerdeira, L., Rodríguez-Martínez, F. J., and GómezRodríguez, A. (2015). Ontology matching: A literature review. Expert Systems with Applications, 42(2):949-971.
  33. Pollack, J. B. (1990). Recursive distributed representations. Artificial Intelligence, 46:77-105.
  34. Rahm, E. (2011). Towards large-scale schema and ontology matching. In Schema matching and mapping, pages 3-27. Springer.
  35. Rahm, E. and Bernstein, P. A. (2001). A survey of approaches to automatic schema matching. The VLDB Journal, 10(4).
  36. Shvaiko, P. and Euzenat, J. (2013). Ontology matching: state of the art and future challenges. IEEE Transactions on Knowledge and Data Engineering, 25(1):158-176.
  37. Sperduti, A. (1993). On some stability properties of the lraam model. Technical report, International Computer Science Institute.
  38. Zdravkovic, M., Trajanovic, M., and Panetto, H. (2014). Enabling interoperability as a property of ubiquitous systems: towards the theory of interoperability-ofeverything. In 4th International Conference on Information Society and Technology, ICIST 2014, volume 1, pages 240-247, Kopaonik, Serbia.
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Paper Citation


in Harvard Style

Ludolph H., Kropf P. and Babin G. (2017). A LRAAM-based Partial Order Function for Ontology Matching in the Context of Service Discovery . In Proceedings of the 7th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, ISBN 978-989-758-243-1, pages 421-431. DOI: 10.5220/0006294904210431


in Bibtex Style

@conference{closer17,
author={Hendrik Ludolph and Peter Kropf and Gilbert Babin},
title={A LRAAM-based Partial Order Function for Ontology Matching in the Context of Service Discovery},
booktitle={Proceedings of the 7th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,},
year={2017},
pages={421-431},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006294904210431},
isbn={978-989-758-243-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,
TI - A LRAAM-based Partial Order Function for Ontology Matching in the Context of Service Discovery
SN - 978-989-758-243-1
AU - Ludolph H.
AU - Kropf P.
AU - Babin G.
PY - 2017
SP - 421
EP - 431
DO - 10.5220/0006294904210431